class_docstr: Constrains to a real-valued tensor where the elements are monotonically
  increasing along the `event_shape` dimension.
code: def check(self, value):
      if value.ndim == 0:
          return torch.tensor(False, device=value.device)
      elif value.shape[-1] == 1:
          return torch.ones_like(value[..., 0], dtype=bool)
      else:
          return torch.all(value[..., 1:] > value[..., :-1], dim=-1)
  
imports: from torch.distributions.constraints import *
  import torch
  from torch.distributions.constraints import Constraint, independent, lower_cholesky, positive, positive_definite
  from torch.distributions.constraints import __all__
label_desc: Use image node_id 1 for calling the _OrderedVector obj's underlying member method code with example usage: obj.check(value) and returns: torch, torch, torch